Chebyshev polynomial approximation to approximate partial differential equations

This paper suggests a simple method based on Chebyshev approximation at Chebyshev nodes to approximate partial differential equations. The methodology simply consists in determining the value function by using a set of nodes and basis functions. We provide two examples. Pricing an European option and determining the best policy for chatting down a machinery. The suggested method is flexible, easy to program and efficient. It is also applicable in other fields, providing efficient solutions to complex systems of partial differential equations.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

The Rebound Effect with Energy Production: A Partial Equilibrium Analysis

Rebound is the extent to which improvements in energy efficiency fail to translate fully into reductions in energy use because of the implicit fall in the price of energy, when measured in efficiency units. This paper discusses aspects of the rebound effect that are introduced once energy is considered as a domestically produced commodity. A partial equilibrium approach is adopted in order to incorporate both energy use and production in a conceptually tractable way. The paper explores analytically two interesting results revealed in previous numerical simulations. The first is the possibility that energy use could fall by more than the implied improvement in efficiency. This corresponds to negative rebound. The second is the finding that the short-run rebound value can be greater than the corresponding long-run value.

IInflation and Globalisation: A Dynamic Factor Model with Stochastic Volatility

National inflation rates reflect domestic and international (regional and global) influences. The relative importance of these components remains a controversial empirical issue. We extend the literature on inflation co-movement by utilising a dynamic factor model with stochastic volatility to account for shifts in the variance of inflation and endogenously determined regional groupings. We find that most of inflation variability is explained by the country specific disturbance term. Nevertheless, the contribution of the global component in explaining industrialised countries’ inflation rates has increased over time.

The Rise and Fall of the ABS Market

The nancial crisis has raised some concern about the quality of information available on some traded assets on the securities markets to market participants and regulators. Asset-backed securitization in general got partial blame for the paucity of liquidity on bank balance sheets and the consequent credit crunch. After the Asset-Backed Security (ABS) market fell to near inactivity in 2009, the US federal government's Term Asset-Backed Securities Loan Facility (TALF) provided backing and a boost to the issuance of asset-backed securitization. In this market condition, given the nature of ABS, it is di¢ cult for them not to be relatively illiquid, and this has resulted in unacceptable levels of market risk for most investors. Their liquidity before the crisis was driven by a market in continuous expansion, fed by Special Purpose Vehicle (SPV), Conduits, and other low capitalized term-transformation vehicles. Nowadays, the industry is concerned with the ongoing ABS reforms and how these will be implemented. This article reviews the ABS market in the last decade and the possible consequences of the recent regulatory proposals. It proposes a retention policy and the institution of a new nancial body to supervise the quality of the security in an ABS pool, its liquidity, and the model risk implied by the issuer's valuation model.

Partial Equal Treatment in Wage Offers

We analyse a labour matching model with wage posting, where- refl ecting institutional constraints-fi rms cannot dfferentiate their wage offers within certain subsets of workers. Inter alia, we find that the presence of impersonal wage offers leads to wage compression, which propagates to the wages for high productivity workers who receive personalised offers.

Stochastic Choice and Consideration Sets

We model a boundedly rational agent who suffers from limited attention. The agent considers each feasible alternative with a given (unobservable) probability, the attention parameter, and then chooses the alternative that maximises a preference relation within the set of considered alternatives. We show that this random choice rule is the only one for which the impact of removing an alternative on the choice probability of any other alternative is asymmetric and menu independent. Both the preference relation and the attention parameters are identi fied uniquely by stochastic choice data.

Partial Knowledge Restrictions on theTwo-Stage Threshold Model of Choice

In the context of the two-stage threshold model of decision making, with the agent’s choices determined by the interaction Of three “structural variables,” we study the restrictions on behavior that arise when one or more variables are xogenously known. Our results supply necessary and sufficient conditions for consistency with the model for all possible states of partial Knowledge, and for both single- and multivalued choice functions.

Stochastic Complementarity

Classical definitions of complementarity are based on cross price elasticities, and so they do not apply, for example, when goods are free. This context includes many relevant cases such as online newspapers and public attractions. We look for a complementarity notion that does not rely on price variation and that is: behavioural (based only on observable choice data); and model-free (valid whether the agent is rational or not). We uncover a conflict between properties that complementarity should intuitively possess. We discuss three ways out of the impossibility.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.